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    "## GeostatsPy: Vairogram Modeling for Subsurface Data Analytics in Python \n",
    "\n",
    "\n",
    "### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "\n",
    "##### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n",
    "\n",
    "\n",
    "### PGE 383 Exercise: Variogram Modeling with GeostatsPy\n",
    "\n",
    "Here's a simple workflow on detecting the major spatial continuity directions in a spatial dataset with variogram analysis. This information is essential to optimum well placement and prectiction away from wells.  First let's explain the concept of spatial continuity and the variogram.\n",
    "\n",
    "#### Spatial Continuity \n",
    "\n",
    "**Spatial Continuity** is the correlation between values over distance.\n",
    "\n",
    "* No spatial continuity – no correlation between values over distance, random values at each location in space regardless of separation distance.\n",
    "\n",
    "* Homogenous phenomenon have perfect spatial continuity, since all values as the same (or very similar) they are correlated. \n",
    "\n",
    "We need a statistic to quantify spatial continuity! A convenient method is the Semivariogram.\n",
    "\n",
    "#### The Semivariogram\n",
    "\n",
    "Function of difference over distance.\n",
    "\n",
    "* The expected (average) squared difference between values separated by a lag distance vector (distance and direction), $h$:\n",
    "\n",
    "\\begin{equation}\n",
    "\\gamma(\\bf{h}) = \\frac{1}{2 N(\\bf{h})} \\sum^{N(\\bf{h})}_{\\alpha=1} (z(\\bf{u}_\\alpha) - z(\\bf{u}_\\alpha + \\bf{h}))^2  \n",
    "\\end{equation}\n",
    "\n",
    "where $z(\\bf{u}_\\alpha)$ and $z(\\bf{u}_\\alpha + \\bf{h})$ are the spatial sample values at tail and head locations of the lag vector respectively.\n",
    "\n",
    "* Calculated over a suite of lag distances to obtain a continuous function.\n",
    "\n",
    "* the $\\frac{1}{2}$ term converts a variogram into a semivariogram, but in practice the term variogram is used instead of semivariogram.\n",
    "* We prefer the semivariogram because it relates directly to the covariance function, $C_x(\\bf{h})$ and univariate variance, $\\sigma^2_x$:\n",
    "\n",
    "\\begin{equation}\n",
    "C_x(\\bf{h}) = \\sigma^2_x - \\gamma(\\bf{h})\n",
    "\\end{equation}\n",
    "\n",
    "Note the correlogram is related to the covariance function as:\n",
    "\n",
    "\\begin{equation}\n",
    "\\rho_x(\\bf{h}) = \\frac{C_x(\\bf{h})}{\\sigma^2_x}\n",
    "\\end{equation}\n",
    "\n",
    "The correlogram provides of function of the $\\bf{h}-\\bf{h}$ scatter plot correlation vs. lag offset $\\bf{h}$.  \n",
    "\n",
    "\\begin{equation}\n",
    "-1.0 \\le \\rho_x(\\bf{h}) \\le 1.0\n",
    "\\end{equation}\n",
    "\n",
    "#### Variogram Observations\n",
    "\n",
    "The following are common observations for variograms that should assist with their practical use.\n",
    "\n",
    "##### Observation \\#1 - As distance increases, variability increase (in general).\n",
    "\n",
    "This is common since in general, over greater distance offsets, there is often more difference between the head and tail samples.\n",
    "\n",
    "In some cases, such as with spatial cyclicity of the hole effect variogram model the variogram may have negative slope over somelag distance intervals\n",
    "\n",
    "Negative slopes at lag distances greater than half the data extent are often caused by too few pairs for a reliable variogram calculation\n",
    "\n",
    "##### Observation \\#2 - Calculated with over all possible pairs separated by lag vector, $\\bf{𝐡}$.\n",
    "\n",
    "We scan through the entire data set, searching for all possible pair combinations with all other data.  We then calculate the variogram as one half the expectation of squared difference between all pairs.\n",
    "\n",
    "More pairs results in a more reliable measure.\n",
    "\n",
    "##### Observation \\#3 - Need to plot the sill to know the degree of correlation.\n",
    "\n",
    "**Sill** is the variance, $\\sigma^2_x$\n",
    "\n",
    "Given stationarity of the variance, $\\sigma^2_x$, and variogram $\\gamma(\\bf{h})$:\n",
    "\n",
    "we can define the covariance function:\n",
    "\n",
    "\\begin{equation}\n",
    "C_x(\\bf{h}) = \\sigma^2_x - \\gamma(\\bf{h})\n",
    "\\end{equation}\n",
    "\n",
    "The covariance measure is a measure of similarity over distance (the mirror image of the variogram as shown by the equation above).\n",
    "\n",
    "Given a standardized distribution $\\sigma^2_x = 1.0$, the covariance, $C_x(\\bf{h})$, is equal to the correlogram, $\\rho_x(\\bf{h})$: \n",
    "\n",
    "\\begin{equation}\n",
    "\\rho_x(\\bf{h}) = \\sigma^2_x - \\gamma(\\bf{h})\n",
    "\\end{equation}\n",
    "\n",
    "##### Observation \\#4 - The lag distance at which the variogram reaches the sill is know as the range.\n",
    "\n",
    "At the range, knowing the data value at the tail location provides no information about a value at the head location of the lag distance vector.\n",
    "\n",
    "##### Observation \\#5 - The nugget effect, a discontinuity at the origin\n",
    "\n",
    "Sometimes there is a discontinuity in the variogram at distances less than the minimum data spacing.  This is known as **nugget effect**.\n",
    "\n",
    "The ratio of nugget / sill, is known as relative nugget effect (%). Modeled as a discontinuity with no correlation structure that at lags, $h \\gt \\epsilon$, an infinitesimal lag distance, and perfect correlation at $\\bf{h} = 0$.\n",
    "Caution when including nuggect effect in the variogram model as measurement error, mixing populations cause apparent nugget effect\n",
    "\n",
    "This exercise demonstrates the semivariogram calculation with GeostatsPy. The steps include:\n",
    "\n",
    "1. generate a 2D model with sequential Gaussian simulation\n",
    "2. sample from the simulation\n",
    "3. calculate and visualize experimental semivariograms\n",
    "\n",
    "#### Detecting Directions of Continuity\n",
    "\n",
    "Spatial continuity can be described with nested spatial continuity models:\n",
    "\n",
    "\\begin{equation}\n",
    "\\Gamma_x(\\bf{h}) = \\sum_{i=1}^{nst} \\gamma_i(\\bf{h})\n",
    "\\end{equation}\n",
    "\n",
    "where $\\Gamma_x(\\bf{h})$ is the nested variogram model resulting from the summation of $nst$ nested variograms  $\\gamma_i(\\bf{h})$.\n",
    "\n",
    "Each one of these variogram structures, $\\gamma_i(\\bf{h})$, is based on a geometric anisotropy model parameterized by the orientation and range in the major and minor directions.  In 2D this is simply an azimuth and ranges, $azi$, $a_{maj}$ and $a_{min}$. Note, the range in the minor direction (orthogonal to the major direction.\n",
    "\n",
    "The geometric anisotropy model assumes that the range in all off-diagonal directions is based on an ellipse with the major and minor axes alligned with and set to the major and minor for the variogram.\n",
    "\n",
    "\\begin{equation}\n",
    "\\bf{h}_i = \\sqrt{\\left(\\frac{r_{maj}}{a_{maj_i}}\\right)^2 + \\left(\\frac{r_{maj}}{a_{maj_i}}\\right)^2}  \n",
    "\\end{equation}\n",
    "\n",
    "Therefore, if we know the major direction, range in major and minor directions, we may completely describe each nested componnent of the complete spatial continuity of the variable of interest, $i = 1,\\dots,nst$.\n",
    "\n",
    "In this workflow we will explore methods to detect directionality from a spatial dataset.\n",
    "\n",
    "#### Objective \n",
    "\n",
    "In the PGE 383: Stochastic Subsurface Modeling class I want to provide hands-on experience with building subsurface modeling workflows. Python provides an excellent vehicle to accomplish this. I have coded a package called GeostatsPy with GSLIB: Geostatistical Library (Deutsch and Journel, 1998) functionality that provides basic building blocks for building subsurface modeling workflows. \n",
    "\n",
    "The objective is to remove the hurdles of subsurface modeling workflow construction by providing building blocks and sufficient examples. This is not a coding class per se, but we need the ability to 'script' workflows working with numerical methods.    \n",
    "\n",
    "#### Getting Started\n",
    "\n",
    "Here's the steps to get setup in Python with the GeostatsPy package:\n",
    "\n",
    "1. Install Anaconda 3 on your machine (https://www.anaconda.com/download/). \n",
    "2. From Anaconda Navigator (within Anaconda3 group), go to the environment tab, click on base (root) green arrow and open a terminal. \n",
    "3. In the terminal type: pip install geostatspy. \n",
    "4. Open Jupyter and in the top block get started by copy and pasting the code block below from this Jupyter Notebook to start using the geostatspy functionality. \n",
    "\n",
    "You will need to copy the data file to your working directory.  They are available here:\n",
    "\n",
    "* Tabular data - sample_data.csv at https://git.io/fh4gm.\n",
    "\n",
    "There are exampled below with these functions. You can go here to see a list of the available functions, https://git.io/fh4eX, other example workflows and source code. \n",
    "\n",
    "#### Load the required libraries\n",
    "\n",
    "The following code loads the required libraries."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import geostatspy.GSLIB as GSLIB                       # GSLIB utilies, visualization and wrapper\n",
    "import geostatspy.geostats as geostats                 # GSLIB methods convert to Python    "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will also need some standard packages. These should have been installed with Anaconda 3."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os                                               # to set current working directory \n",
    "import numpy as np                                      # arrays and matrix math\n",
    "import pandas as pd                                     # DataFrames\n",
    "import matplotlib.pyplot as plt                         # plotting"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If you get a package import error, you may have to first install some of these packages. This can usually be accomplished by opening up a command window on Windows and then typing 'python -m pip install [package-name]'. More assistance is available with the respective package docs.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "#### Set the working directory\n",
    "\n",
    "I always like to do this so I don't lose files and to simplify subsequent read and writes (avoid including the full address each time).  Also, in this case make sure to place the required (see above) GSLIB executables in this directory or a location identified in the environmental variable *Path*."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.chdir(\"d:/PGE383\")                                   # set the working directory"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Loading Tabular Data\n",
    "\n",
    "Here's the command to load our comma delimited data file in to a Pandas' DataFrame object. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Facies</th>\n",
       "      <th>Porosity</th>\n",
       "      <th>Perm</th>\n",
       "      <th>AI</th>\n",
       "    </tr>\n",
       "  </thead>\n",
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       "      <th>0</th>\n",
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       "      <th>3</th>\n",
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       "      <td>2534.551236</td>\n",
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       "  </tbody>\n",
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      ],
      "text/plain": [
       "   Unnamed: 0      X      Y  Facies  Porosity        Perm           AI\n",
       "0           0  100.0  900.0     0.0  0.101319    1.996868  5590.417154\n",
       "1           1  100.0  800.0     1.0  0.147676   10.711789  3470.845666\n",
       "2           2  100.0  700.0     1.0  0.145912   17.818143  3586.988513\n",
       "3           3  100.0  600.0     1.0  0.186167  217.109365  3732.114787\n",
       "4           4  100.0  500.0     1.0  0.146088   16.717367  2534.551236"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"sample_data_MV_biased.csv\")                     # read a .csv file in as a DataFrame\n",
    "#print(df.iloc[0:5,:])                                  # display first 4 samples in the table as a preview\n",
    "df.head()                                               # we could also use this command for a table preview "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will work with all facies pooled together. I wanted to simplify this workflow and focus more on spatial continuity direction detection. Finally, by not using facies we do have more samples to support our statistical inference. Most often facies are essential in the subsurface model. Don't worry we will check if this is reasonable in a bit.   \n",
    "\n",
    "You are welcome to repeat this workflow on a by-facies basis.  The following code could be used to build DataFrames ('df_sand' and 'df_shale') for each facies.\n",
    "\n",
    "```p\n",
    "df_sand = pd.DataFrame.copy(df[df['Facies'] == 1]).reset_index()  # copy only 'Facies' = sand records\n",
    "df_shale = pd.DataFrame.copy(df[df['Facies'] == 0]).reset_index() # copy only 'Facies' = shale records\n",
    "```\n",
    "\n",
    "Let's look at summary statistics for all facies combined:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>count</th>\n",
       "      <th>mean</th>\n",
       "      <th>std</th>\n",
       "      <th>min</th>\n",
       "      <th>25%</th>\n",
       "      <th>50%</th>\n",
       "      <th>75%</th>\n",
       "      <th>max</th>\n",
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       "      <th>Unnamed: 0</th>\n",
       "      <td>368.0</td>\n",
       "      <td>293.260870</td>\n",
       "      <td>169.058258</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>150.500000</td>\n",
       "      <td>296.000000</td>\n",
       "      <td>439.500000</td>\n",
       "      <td>586.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>X</th>\n",
       "      <td>368.0</td>\n",
       "      <td>499.565217</td>\n",
       "      <td>289.770794</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>240.000000</td>\n",
       "      <td>500.000000</td>\n",
       "      <td>762.500000</td>\n",
       "      <td>990.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Y</th>\n",
       "      <td>368.0</td>\n",
       "      <td>520.644022</td>\n",
       "      <td>277.412187</td>\n",
       "      <td>9.000000</td>\n",
       "      <td>269.000000</td>\n",
       "      <td>539.000000</td>\n",
       "      <td>769.000000</td>\n",
       "      <td>999.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Facies</th>\n",
       "      <td>368.0</td>\n",
       "      <td>0.597826</td>\n",
       "      <td>0.491004</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Porosity</th>\n",
       "      <td>368.0</td>\n",
       "      <td>0.127026</td>\n",
       "      <td>0.030642</td>\n",
       "      <td>0.041122</td>\n",
       "      <td>0.103412</td>\n",
       "      <td>0.125842</td>\n",
       "      <td>0.148623</td>\n",
       "      <td>0.210258</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Perm</th>\n",
       "      <td>368.0</td>\n",
       "      <td>85.617362</td>\n",
       "      <td>228.362654</td>\n",
       "      <td>0.094627</td>\n",
       "      <td>2.297348</td>\n",
       "      <td>10.377292</td>\n",
       "      <td>50.581288</td>\n",
       "      <td>1991.097723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AI</th>\n",
       "      <td>368.0</td>\n",
       "      <td>4791.736646</td>\n",
       "      <td>974.560569</td>\n",
       "      <td>1981.177309</td>\n",
       "      <td>4110.728374</td>\n",
       "      <td>4713.325533</td>\n",
       "      <td>5464.043562</td>\n",
       "      <td>7561.250336</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            count         mean         std          min          25%  \\\n",
       "Unnamed: 0  368.0   293.260870  169.058258     0.000000   150.500000   \n",
       "X           368.0   499.565217  289.770794     0.000000   240.000000   \n",
       "Y           368.0   520.644022  277.412187     9.000000   269.000000   \n",
       "Facies      368.0     0.597826    0.491004     0.000000     0.000000   \n",
       "Porosity    368.0     0.127026    0.030642     0.041122     0.103412   \n",
       "Perm        368.0    85.617362  228.362654     0.094627     2.297348   \n",
       "AI          368.0  4791.736646  974.560569  1981.177309  4110.728374   \n",
       "\n",
       "                    50%          75%          max  \n",
       "Unnamed: 0   296.000000   439.500000   586.000000  \n",
       "X            500.000000   762.500000   990.000000  \n",
       "Y            539.000000   769.000000   999.000000  \n",
       "Facies         1.000000     1.000000     1.000000  \n",
       "Porosity       0.125842     0.148623     0.210258  \n",
       "Perm          10.377292    50.581288  1991.097723  \n",
       "AI          4713.325533  5464.043562  7561.250336  "
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe().transpose()                          # summary table of sand only DataFrame statistics"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's transform the porosity and permeaiblity data to standard normal (mean = 0.0, standard deviation = 1.0, Gaussian shape). This is required for sequential Gaussian simulation (common target for our variogram models) and the Gaussian transform assists with outliers and provides more interpretable variograms. \n",
    "\n",
    "Let's look at the inputs for the GeostatsPy nscore program.  Note the output include an ndarray with the transformed values (in the same order as the input data in Dataframe 'df' and column 'vcol'), and the transformation table in original values and also in normal score values. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<function geostatspy.geostats.nscore(df, vcol, wcol=None, ismooth=False, dfsmooth=None, smcol=0, smwcol=0)>"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "geostats.nscore                                         # see the input parameters required by the nscore function"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The following command will transform the Porosity and Permeabilty to standard normal. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Transform to Gaussian by Facies\n",
    "df['NPor'], tvPor, tnsPor = geostats.nscore(df, 'Porosity') # nscore transform for all facies porosity \n",
    "df['NPerm'], tvPermSand, tnsPermSand = geostats.nscore(df, 'Perm')  # nscore transform for all facies permeability"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's look at the updated DataFrame to make sure that we now have the normal score porosity and permeability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>X</th>\n",
       "      <th>Y</th>\n",
       "      <th>Facies</th>\n",
       "      <th>Porosity</th>\n",
       "      <th>Perm</th>\n",
       "      <th>AI</th>\n",
       "      <th>NPor</th>\n",
       "      <th>NPerm</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>100.0</td>\n",
       "      <td>900.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.101319</td>\n",
       "      <td>1.996868</td>\n",
       "      <td>5590.417154</td>\n",
       "      <td>-0.749088</td>\n",
       "      <td>-0.767247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>100.0</td>\n",
       "      <td>800.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.147676</td>\n",
       "      <td>10.711789</td>\n",
       "      <td>3470.845666</td>\n",
       "      <td>0.653263</td>\n",
       "      <td>0.017030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>100.0</td>\n",
       "      <td>700.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.145912</td>\n",
       "      <td>17.818143</td>\n",
       "      <td>3586.988513</td>\n",
       "      <td>0.611663</td>\n",
       "      <td>0.336607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>100.0</td>\n",
       "      <td>600.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.186167</td>\n",
       "      <td>217.109365</td>\n",
       "      <td>3732.114787</td>\n",
       "      <td>1.993601</td>\n",
       "      <td>1.211919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>100.0</td>\n",
       "      <td>500.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.146088</td>\n",
       "      <td>16.717367</td>\n",
       "      <td>2534.551236</td>\n",
       "      <td>0.628172</td>\n",
       "      <td>0.279461</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unnamed: 0      X      Y  Facies  Porosity        Perm           AI  \\\n",
       "0           0  100.0  900.0     0.0  0.101319    1.996868  5590.417154   \n",
       "1           1  100.0  800.0     1.0  0.147676   10.711789  3470.845666   \n",
       "2           2  100.0  700.0     1.0  0.145912   17.818143  3586.988513   \n",
       "3           3  100.0  600.0     1.0  0.186167  217.109365  3732.114787   \n",
       "4           4  100.0  500.0     1.0  0.146088   16.717367  2534.551236   \n",
       "\n",
       "       NPor     NPerm  \n",
       "0 -0.749088 -0.767247  \n",
       "1  0.653263  0.017030  \n",
       "2  0.611663  0.336607  \n",
       "3  1.993601  1.211919  \n",
       "4  0.628172  0.279461  "
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()                                               # preview sand DataFrame with nscore transforms"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "That looks good! One way to check is to see if the relative magnitudes of the normal score transformed values match the original values.  e.g. that the normal score transform of 0.10 porosity normal score is less than the normal score transform of 0.14 porsity.  Also, the normal score transform of values close to the mean value should be close to 0.0 \n",
    "\n",
    "Let's also check the original and transformed sand and shale porosity distributions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(221)                                        # plot original sand and shale porosity histograms\n",
    "plt.hist(df['Porosity'], facecolor='red',bins=np.linspace(0.0,0.25,1000),histtype=\"stepfilled\",alpha=0.2,density=True,cumulative=True,edgecolor='black',label='Original')\n",
    "plt.xlim([0.05,0.25]); plt.ylim([0,1.0])\n",
    "plt.xlabel('Porosity (fraction)'); plt.ylabel('Frequency'); plt.title('Porosity')\n",
    "plt.legend(loc='upper left')\n",
    "plt.grid(True)\n",
    "\n",
    "plt.subplot(222)  \n",
    "plt.hist(df['NPor'], facecolor='blue',bins=np.linspace(-3.0,3.0,1000),histtype=\"stepfilled\",alpha=0.2,density=True,cumulative=True,edgecolor='black',label = 'Trans')\n",
    "plt.xlim([-3.0,3.0]); plt.ylim([0,1.0])\n",
    "plt.xlabel('Porosity (fraction)'); plt.ylabel('Frequency'); plt.title('Nscore Porosity')\n",
    "plt.legend(loc='upper left')\n",
    "plt.grid(True)\n",
    "\n",
    "plt.subplot(223)                                        # plot nscore transformed sand and shale histograms\n",
    "plt.hist(df['Perm'], facecolor='red',bins=np.linspace(0.0,1000.0,100000),histtype=\"stepfilled\",alpha=0.2,density=True,cumulative=True,edgecolor='black',label='Original')\n",
    "plt.xlim([0.0,1000.0]); plt.ylim([0,1.0])\n",
    "plt.xlabel('Porosity (fraction)'); plt.ylabel('Frequency'); plt.title('Permeability')\n",
    "plt.legend(loc='upper left')\n",
    "plt.grid(True)\n",
    "\n",
    "plt.subplot(224)                                        # plot nscore transformed sand and shale histograms\n",
    "plt.hist(df['NPerm'], facecolor='blue',bins=np.linspace(-3.0,3.0,100000),histtype=\"stepfilled\",alpha=0.2,density=True,cumulative=True,edgecolor='black',label = 'Trans')\n",
    "plt.xlim([-3.0,3.0]); plt.ylim([0,1.0])\n",
    "plt.xlabel('Permeability (mD)'); plt.ylabel('Frequency'); plt.title('Nscore Permeability')\n",
    "plt.legend(loc='upper left')\n",
    "plt.grid(True)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=2.2, wspace=0.2, hspace=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The normal score transform has correctly transformed the porosity and permeability to standard normal.\n",
    "\n",
    "#### Method \\#1: Ocular Inspection of Posted Data\n",
    "\n",
    "Data visualization is very useful to detect patterns. Our brains are very good at pattern detection. I promote quantitative methods and recognize issues with cognitive bias, but it is important to recognize the value is expert intepretation based on data visualization.\n",
    "\n",
    "* This data visualization will also be important to assist with parameter selection for the quantitative methods later.\n",
    "\n",
    "Let's plot the location maps of normal score transforms of porosity and permeability for all facies. We will also include a cross plot of the nscore permeability vs. porosity colored by facies to aid with comparison in spatial features between the porosity and permeability data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 5 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cmap = plt.cm.plasma                    # color map\n",
    "plt.subplot(131)\n",
    "GSLIB.locmap_st(df,'X','Y','NPor',0,1000,0,1000,-3,3,'Nscore Porosity - All Facies','X (m)','Y (m)','Nscore Porosity',cmap)\n",
    "\n",
    "plt.subplot(132)\n",
    "GSLIB.locmap_st(df,'X','Y','NPerm',0,1000,0,1000,-3,3,'Nscore Permeability - All Facies','X (m)','Y (m)','Nscore Permeability',cmap)\n",
    "\n",
    "plt.subplot(133)\n",
    "facies = df['Facies'].values +0.01\n",
    "plt.scatter(df['NPor'],df['NPerm'],c = facies,edgecolor = 'black',cmap = plt.cm.inferno)\n",
    "#plt.plot([-3,3],[-3,3],color = 'black')\n",
    "plt.xlabel(r'Nscore Porosity')\n",
    "plt.ylabel(r'Nscore Permeability')\n",
    "plt.title('Nscore Permeability vs. Porosity')\n",
    "plt.xlim([-3,3])\n",
    "plt.ylim([-3,3])\n",
    "plt.grid(True)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=0.8, wspace=0.5, hspace=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do you see?  Here's my observations:\n",
    "\n",
    "* there is a high degree of spatial agreement between porosity and permeability, this is supported by the high correlation evident in the cross plot.\n",
    "* there are no discontinuities that could suggest that facies represent a distinct change, rather the porosity and permeability seem continuous and the assigned facies are a truncation of their continous behavoir, we doing 'ok' with no facies\n",
    "* suspect a 045 azimuth major direction of continuity (up - right)\n",
    "* there may be cycles in the 135 azimuth \n",
    "* there will not likely be a nugget effect, but there is an hint of some short scale discontinuity?\n",
    "\n",
    "**Do you agree?** If you have a different observations, drop me a line at mpyrcz@austin.utexas.edu and I'll add to this lesson with credit.\n",
    "\n",
    "#### Method \\#2: Variogram Maps\n",
    "\n",
    "Let's try out variogram maps. \n",
    "\n",
    "* I realized that I had not coded variogram maps in Python, so I just did it and added it to GeostatsPy.  I have added if here temporarily to support my students completely their assignments. I'm teaching this week at a company and it is safer not to update the package until I have time to test it.\n",
    "\n",
    "The inputs include: \n",
    "\n",
    "* **input data** - DataFrame, 'df', and columns for x, y and property of interest, 'x', 'y' and 'vcol', \n",
    "* **variogram map parameters** - number of cells in each direction to search, 'nxlag', nylag', the cell size / lag distance, 'dxlag' and 'dylag'''\n",
    "* **search** - the minimum number of pairs reuqired to assign a result, 'mnpairs'\n",
    "* **normalization** - 1 for standardize variance to 1.0 and 0 for not\n",
    "\n",
    "The output is a 2D ndarray with the variogram map and the number of pairs."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The shape of the output is (23, 23)\n"
     ]
    }
   ],
   "source": [
    "vmap, npmap = geostats.varmapv(df,'X','Y','NPor',tmin=-999,tmax=999,nxlag=11,nylag=11,dxlag=50,dylag=50,minnp=1,isill=1)\n",
    "\n",
    "plt.subplot(121)\n",
    "GSLIB.pixelplt_st(vmap,-575,575,-575,575,50.0,0,1.6,'Nscore Porosity Variogram Map','X(m)','Y(m)','Nscore Variogram',cmap)\n",
    "\n",
    "plt.subplot(122)\n",
    "GSLIB.pixelplt_st(npmap,-575,575,-575,575,50.0,0,900,'Nscore Porosity Variogram Map Number of Pairs','X(m)','Y(m)','Number of Pairs',cmap)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=3.0, top=1.2, wspace=0.2, hspace=0.2)\n",
    "plt.show()\n",
    "\n",
    "print('The shape of the output is ' + str(vmap.shape))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Notice that the output ndarray is 23, 23 cells? We asked for the number of cells to extend in each direction, 11 and 11 in x and y.  The map has an origin (zero distance) cell in the middle and extends 11 in both positive and negative directions.  So we have 2*$nx$ + 1, 2*$ny$ + 1 cells in the resulting variogram map and the $xmin = -1 * (nx * x_{cellsize} + \\frac{1}{2} x_{cellsize})$ and the $xmax = nx * x_{cellsize} + \\frac{1}{2} x_{cellsize}$"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "What do you think of this variogram map? These are my observations:\n",
    "\n",
    "* major continuity direction is at azimuth 045\n",
    "* there is a high degree of geometric anisotropy\n",
    "* there is cyclicity in the 135 direction \n",
    "* there may be some cyclicity in the 045 direction\n",
    "\n",
    "From this variogram map we can immediately see directionality in our spatial data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Method \\#3: Experimental Variograms\n",
    "\n",
    "Another method for exploring spatial data directionality is the calculation of multiple experimental variograms for a variety of directions.\n",
    "\n",
    "We can use the location maps to help determine good variogram calculation parameters.\n",
    "\n",
    "```p\n",
    "tmin = -9999.; tmax = 9999.; \n",
    "lag_dist = 100.0; lag_tol = 50.0; nlag = 7; bandh = 9999.9; azi = azi; atol = 22.5; isill = 1\n",
    "```\n",
    "* **tmin**, **tmax** are trimming limits - set to have no impact, no need to filter the data\n",
    "* **lag_dist**, **lag_tol** are the lag distance, lag tolerance - set based on the common data spacing (100m) and tolerance as 100% of lag distance for additonal smoothing\n",
    "* **nlag** is number of lags - set to extend just past 50 of the data extent\n",
    "* **bandh** is the horizontal band width - set to have no effect\n",
    "* **azi** is the azimuth -  it has not effect since we set atol, the azimuth tolerance, to 90.0\n",
    "* **isill** is a boolean to standardize the distribution to a variance of 1 - it has no effect since the nscore transform sets the variance to 1.0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "tmin = -9999.; tmax = 9999.                             # no trimming \n",
    "lag_dist = 100.0; lag_tol = 100.0; nlag = 7;            # maximum lag is 700m and tolerance > 1/2 lag distance for smoothing\n",
    "bandh = 9999.9; atol = 22.5                             # no bandwidth, directional variograms\n",
    "isill = 1                                               # standardize sill\n",
    "azi_mat = [0,22.5,45,67.5,90,112.5,135,157.5]           # directions in azimuth to consider"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's try running these variograms and visualizing them on separate plots.  I'll demonstrate a method to promgramtically loop over each direction for efficiency (and code brevity).\n",
    "\n",
    "* we have the direction in the list called 'azi_mat'\n",
    "* we use the command:\n",
    "```p\n",
    "for iazi in range(0,len(azi_mat)): \n",
    "```\n",
    "to loop over all the elements in the list with index 'iazi'\n",
    "\n",
    "* we run the variogram calculation and store the reuslts in 2D arrays, iy is direction, ix is the lag\n",
    "* we use subplots with the 'iazi' index to add each plot\n",
    "\n",
    "```p\n",
    "    plt.subplot(4,2,iazi+1)\n",
    "```\n",
    "we add one because the plot index must be $1,\\ldots,n$, but arrays / list index as $0,\\ldots,n-1$ in Python."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Arrays to store the results\n",
    "lag = np.zeros((len(azi_mat),nlag+2)); gamma = np.zeros((len(azi_mat),nlag+2)); npp = np.zeros((len(azi_mat),nlag+2));\n",
    "\n",
    "for iazi in range(0,len(azi_mat)):                      # Loop over all directions\n",
    "    lag[iazi,:], gamma[iazi,:], npp[iazi,:] = geostats.gamv(df,\"X\",\"Y\",\"NPor\",tmin,tmax,lag_dist,lag_tol,nlag,azi_mat[iazi],atol,bandh,isill)\n",
    "    plt.subplot(4,2,iazi+1)\n",
    "    plt.plot(lag[iazi,:],gamma[iazi,:],'x',color = 'black',label = 'Azimuth ' +str(azi_mat[iazi]))\n",
    "    plt.plot([0,2000],[1.0,1.0],color = 'black')\n",
    "    plt.xlabel(r'Lag Distance $\\bf(h)$, (m)')\n",
    "    plt.ylabel(r'$\\gamma \\bf(h)$')\n",
    "    plt.title('Directional NSCORE Porosity Variogram')\n",
    "    plt.xlim([0,700])\n",
    "    plt.ylim([0,1.8])\n",
    "    plt.legend(loc='upper left')\n",
    "    plt.grid(True)\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.0, top=4.2, wspace=0.2, hspace=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The directional variograms provide a very clear image of directionality. The ranges vary from 300m, 500m to zonal anisotropy, to 500m, 350m, 280m, 250m and finally 280m.  We are observing the actually spatial continuity ellipse by exploring a variety of directions! \n",
    "\n",
    "* We can observe that Azimuth 045 is the major direction and Azimuth 135 is the minor direction.\n",
    "\n",
    "This is a very powerful tool for exploring directionality in spatial datasets.\n",
    "\n",
    "#### Variogram Modeling\n",
    "\n",
    "From above we can identify 045 as the major direction and 135 as the minor direction. We must build a single 2D nested variogram model based on the experiential variograms in each 045 and 135 directions.  First, let's look at these two experimental variograms again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplot(1,2,1)\n",
    "plt.plot(lag[2,:],gamma[2,:],'x',color = 'black',label = 'Azimuth ' +str(azi_mat[2]))\n",
    "plt.plot([0,2000],[1.0,1.0],color = 'black')\n",
    "plt.xlabel(r'Lag Distance $\\bf(h)$, (m)')\n",
    "plt.ylabel(r'$\\gamma \\bf(h)$')\n",
    "plt.title('Directional NSCORE Porosity Variogram')\n",
    "plt.xlim([0,700])\n",
    "plt.ylim([0,1.8])\n",
    "plt.legend(loc='upper left')\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.plot(lag[6,:],gamma[6,:],'x',color = 'black',label = 'Azimuth ' +str(azi_mat[6]))\n",
    "plt.plot([0,2000],[1.0,1.0],color = 'black')\n",
    "plt.xlabel(r'Lag Distance $\\bf(h)$, (m)')\n",
    "plt.ylabel(r'$\\gamma \\bf(h)$')\n",
    "plt.title('Directional NSCORE Porosity Variogram')\n",
    "plt.xlim([0,700])\n",
    "plt.ylim([0,1.8])\n",
    "plt.legend(loc='upper left')\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.2, top=1.6, wspace=0.2, hspace=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will assume these models will be applied in sequential Gaussian simulation; therefore, we must model to the sill (or the global distribution will not be reproduced over the realizations).  We will also not use cyclicity for now, as we are just getting started.  \n",
    "\n",
    "* Let's build a reasonable model to the sill.\n",
    "\n",
    "##### make_variogram function\n",
    "\n",
    "We use the make_variogram function to make a variogram model \n",
    "\n",
    "* a dictionary for compact storage of the variogram model parameters to pass into plotting (below), kriging and simulation methods \n",
    "\n",
    "The variogram model parameter include:\n",
    "\n",
    "* **nug** - nugget effect contribution to sill\n",
    "* **nst** - number of nested structures (1 or 2)\n",
    "* **it** - type for this nested structure (1 - spherical, 2 - exponential, 3 - Gaussian)\n",
    "* **cc** - contribution of each nested structure (contributions + nugget must sum to the sill)\n",
    "* **azi** - the azimuth for this nested structure of the major direction, the minor is orthogonal\n",
    "* **hmaj** - the range for this nested structure in the major direction\n",
    "* **hmin** - the range for this nested structure in the minor direction\n",
    "\n",
    "We increment it, cc, azi, hmaj, and hmin for the 1st and 2nd structures\n",
    "\n",
    "* for only 1 structure plus optional nugget, omit the 2nd structure parameters and they will default to $cc2 = 0$, no contribution to the model\n",
    "\n",
    "Here's my model:\n",
    "\n",
    "```p\n",
    "nug = 0.0; nst = 2\n",
    "it1 = 1; cc1 = 0.6; azi1 = 45; hmaj1 = 350; hmin1 = 350                # first structure\n",
    "it2 = 1; cc2 = 0.4; azi2 = 45; hmaj2 = 9999.9; hmin2 = 400             # second structure\n",
    "```\n",
    "\n",
    "Some comments on our model:\n",
    "\n",
    "* we model to the sill of 1.0, since we applied the normal score transform ($nug + cc1 + cc2 = 1.0$)\n",
    "\n",
    "* we used 2 spherical structures to capture zontal anisotropy in the 045 azimuth\n",
    "\n",
    "* since the experimental variogram exceeds the sill with trend or cyclicity we could have attempted trend modeling and then worked with the residual, but we will not do this for workflow brevity and simplicity\n",
    "\n",
    "We input these model parameters to make a variogram model dictionary with the make_variogram function as follows:\n",
    "\n",
    "```p\n",
    "vario = GSLIB.make_variogram(nug,nst,it1,cc1,azi1,hmaj1,hmin1,it2,cc2,azi2,hmaj2,hmin2)\n",
    "```\n",
    "\n",
    "##### vmodel function\n",
    "\n",
    "To plot the variogram we use the vmodel function to project the model in the major and minor directions\n",
    "\n",
    "The inputs for vmodel are:\n",
    "\n",
    "* **nlag** - the number of points along the variogram to calculate for the projection\n",
    "\n",
    "* **xlag** - the size of a lag for the projection\n",
    "\n",
    "* **azm** - the direction of the projection in azimuth (this is all we need since we are working in 2D)\n",
    "\n",
    "* **vario** - the variogram model dictionary from the make_variogram function (above)\n",
    "\n",
    "Note: this function is just for visualization by projecting the variogram model in a direction, so the convention is to use a very small **xlag** and large **nlag** for a high resolution display of the variogram model\n",
    "\n",
    "The outputs from the vmodel program include:\n",
    "\n",
    "* **index** - the lag number for the projection\n",
    "\n",
    "* **lag distance** - the distance offset along the projection (the **h** in the variogram plot)\n",
    "\n",
    "* **variogram** - the variogram value at the lag distance for the projection (the $\\gamma$(**h**) in the variogram plot)\n",
    "\n",
    "* **covariance function** - the covariance function at the lag distance for the projection (for the C(**h**) plot)\n",
    "\n",
    "* **correlogram** - the correlogram at the lag distance for the projection (for the $\\rho$(**h**) plot)\n",
    "\n",
    "We have 2 structures and no nugget effect.  We needed the 2nd structure to capture the zonal anisotropy in the 045 direction.  Let's calculate the variogram model in these directions and plot them with the experimental variograms.   "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      " x,y,z offsets = 7.071067805519558,7.071067818211393\n",
      " x,y,z offsets = 7.071067830903227,-7.071067792827723\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nug = 0.0; nst = 2                                             # 2 nest structure variogram model parameters\n",
    "it1 = 1; cc1 = 0.6; azi1 = 45; hmaj1 = 350; hmin1 = 350\n",
    "it2 = 1; cc2 = 0.4; azi2 = 45; hmaj2 = 9999.9; hmin2 = 400\n",
    "\n",
    "vario = GSLIB.make_variogram(nug,nst,it1,cc1,azi1,hmaj1,hmin1,it2,cc2,azi2,hmaj2,hmin2) # make model object\n",
    "nlag = 70; xlag = 10; azm = 45;                                # project the model in the 045 azimuth\n",
    "index45,h45,gam45,cov45,ro45 = geostats.vmodel(nlag,xlag,azm,vario)\n",
    "azm = 135                                                      # project the model in the 135 azimuth\n",
    "index135,h135,gam135,cov135,ro135 = geostats.vmodel(nlag,xlag,azm,vario)\n",
    "\n",
    "plt.subplot(1,2,1)\n",
    "plt.plot(lag[2,:],gamma[2,:],'x',color = 'black',label = 'Azimuth ' +str(azi_mat[2]))\n",
    "plt.plot([0,2000],[1.0,1.0],color = 'black')\n",
    "plt.plot(h45,gam45,color = 'black')\n",
    "plt.xlabel(r'Lag Distance $\\bf(h)$, (m)')\n",
    "plt.ylabel(r'$\\gamma \\bf(h)$')\n",
    "plt.title('Directional NSCORE Porosity Variogram')\n",
    "plt.xlim([0,700])\n",
    "plt.ylim([0,1.8])\n",
    "plt.legend(loc='upper left')\n",
    "\n",
    "plt.subplot(1,2,2)\n",
    "plt.plot(lag[6,:],gamma[6,:],'x',color = 'black',label = 'Azimuth ' +str(azi_mat[6]))\n",
    "plt.plot([0,2000],[1.0,1.0],color = 'black')\n",
    "plt.plot(h135,gam135,color = 'black')\n",
    "plt.xlabel(r'Lag Distance $\\bf(h)$, (m)')\n",
    "plt.ylabel(r'$\\gamma \\bf(h)$')\n",
    "plt.title('Directional NSCORE Porosity Variogram')\n",
    "plt.xlim([0,700])\n",
    "plt.ylim([0,1.8])\n",
    "plt.legend(loc='upper left')\n",
    "\n",
    "plt.subplots_adjust(left=0.0, bottom=0.0, right=2.2, top=1.6, wspace=0.2, hspace=0.3)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comments\n",
    "\n",
    "This was a basic demonstration of vairogram modeling for spatial continuity analysis. Much more could be done, I have other demonstrations on the basics of working with DataFrames, ndarrays, univariate statistics, plotting data, declustering, data transformations and many other workflows available at https://github.com/GeostatsGuy/PythonNumericalDemos and https://github.com/GeostatsGuy/GeostatsPy. \n",
    "  \n",
    "#### The Author:\n",
    "\n",
    "### Michael Pyrcz, Associate Professor, University of Texas at Austin \n",
    "*Novel Data Analytics, Geostatistics and Machine Learning Subsurface Solutions*\n",
    "\n",
    "With over 17 years of experience in subsurface consulting, research and development, Michael has returned to academia driven by his passion for teaching and enthusiasm for enhancing engineers' and geoscientists' impact in subsurface resource development. \n",
    "\n",
    "For more about Michael check out these links:\n",
    "\n",
    "#### [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)\n",
    "\n",
    "#### Want to Work Together?\n",
    "\n",
    "I hope this content is helpful to those that want to learn more about subsurface modeling, data analytics and machine learning. Students and working professionals are welcome to participate.\n",
    "\n",
    "* Want to invite me to visit your company for training, mentoring, project review, workflow design and / or consulting? I'd be happy to drop by and work with you! \n",
    "\n",
    "* Interested in partnering, supporting my graduate student research or my Subsurface Data Analytics and Machine Learning consortium (co-PIs including Profs. Foster, Torres-Verdin and van Oort)? My research combines data analytics, stochastic modeling and machine learning theory with practice to develop novel methods and workflows to add value. We are solving challenging subsurface problems!\n",
    "\n",
    "* I can be reached at mpyrcz@austin.utexas.edu.\n",
    "\n",
    "I'm always happy to discuss,\n",
    "\n",
    "*Michael*\n",
    "\n",
    "Michael Pyrcz, Ph.D., P.Eng. Associate Professor The Hildebrand Department of Petroleum and Geosystems Engineering, Bureau of Economic Geology, The Jackson School of Geosciences, The University of Texas at Austin\n",
    "\n",
    "#### More Resources Available at: [Twitter](https://twitter.com/geostatsguy) | [GitHub](https://github.com/GeostatsGuy) | [Website](http://michaelpyrcz.com) | [GoogleScholar](https://scholar.google.com/citations?user=QVZ20eQAAAAJ&hl=en&oi=ao) | [Book](https://www.amazon.com/Geostatistical-Reservoir-Modeling-Michael-Pyrcz/dp/0199731446) | [YouTube](https://www.youtube.com/channel/UCLqEr-xV-ceHdXXXrTId5ig)  | [LinkedIn](https://www.linkedin.com/in/michael-pyrcz-61a648a1)  \n",
    "  "
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